Gilbert L Wedekind

51976668, Mar 30, 1993

Jan 2, 1992

7/816876

Gilbert L. Wedekind - Rochester Hills MI

F23N 520
G04D 2300

236 46R

A parameter estimation system (16) automatically determines the relevant thermal and thermodynamic parameters which govern the energy consumption of the climate control system (18) within an enclosure (30). The method of the parameter estimation (16) assembly, using the continuous measurement of various air temperatures, air flows, and energy consumption rates includes the adaptive capability of indirectly learning the relevant thermal and thermodynamic characteristics of both the building enclosure (30) and the climate control system (18), including such thermal parameters as the effective thermal capacitance of the internal walls and contents (53,55) of the enclosure (30), the effective internal heat transfer conductance between the thermal capacitance and the air within the conditioned space (28), the effective external heat transfer conductance between the inside air (28) and the outside air (36) and the efficiency characteristics of the climate control system (18), both inclusive and exclusive of the associated air distribution system (22,32), as a function of its input energy rate. The method also includes a non-linear efficiency model, using the aforementioned thermal parameters, which has the capability of predicting building air temperature, cool down and recovery, and the energy consumption of the climate control system (18) as a function of outside air temperature and the user-specified occupancy comfort schedule (39), thus providing the additional capabilities for determining a building energy rating and for making intelligent energy management decisions associated with optimal operation, maintenance and retrofitting.

51159678, May 26, 1992

Mar 18, 1991

7/670718

Gilbert L. Wedekind - Rochester Hills MI

F23N 520
G05D 2300

236 46R

A computer (37) or microprocessor-based thermostat system (10) for automatically determining and implementing an optimum thermostat setback schedule (80) which, while maintaining a user-specified occupancy comfort schedule (39), minimizes the energy consumption of the climate control system (18) within an enclosure (30). The method of the thermostat assembly (10), using the continuous measurement of various air temperatures, fluid flows, and energy consumption rates includes the adaptive capability of indirectly learning the relevant thermal and thermodynamic characteristics of both the enclosure (30) and the climate control system (18), including such thermal parameters as the effective thermal capacitance of the internal walls and contents (53,55) of the enclosure (30), the effective internal heat transfer conductance between the thermal capacitance and the air within the conditioned space (28), the effective external heat transfer conductance between the inside air (28) and the outside air (36) and the efficiency of the climate control system (18), which includes the associated air distribution system (22, 32), as a function of its input energy rate. The method also includes a non-linear efficiency model, using the aforementioned thermal parameters, which has the capability of predicting, in advance of implementation, the energy consumption of the climate control system (18) as a function of outside air temperature and the user-specified occupancy comfort schedule (39). An optimization scheme is then used to determine the most energy efficient thermostat setback schedule (80) for the current outdoor air temperature, while still satisfying the user-specified occupancy comfort schedule (39).